Overview

Dataset statistics

Number of variables19
Number of observations300000
Missing cells380740
Missing cells (%)6.7%
Total size in memory45.8 MiB
Average record size in memory160.0 B

Variable types

Text19

Alerts

consumption-for-eg-btu-units has constant value "million MMBtu"Constant
generation-units has constant value "thousand megawatthours"Constant
total-consumption-btu-units has constant value "million MMBtu"Constant
consumption-for-eg has 31345 (10.4%) missing valuesMissing
consumption-for-eg-btu has 31345 (10.4%) missing valuesMissing
cost has 241811 (80.6%) missing valuesMissing
generation has 13549 (4.5%) missing valuesMissing
total-consumption has 31345 (10.4%) missing valuesMissing
total-consumption-btu has 31345 (10.4%) missing valuesMissing

Reproduction

Analysis started2026-01-10 22:20:56.671815
Analysis finished2026-01-10 22:21:10.256463
Duration13.58 seconds
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

period
Text

Distinct34
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:10.504076image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2100000
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-12
2nd row2023-05
3rd row2025-09
4th row2023-11
5th row2024-09
ValueCountFrequency (%)
2023-038916
 
3.0%
2024-088906
 
3.0%
2023-068894
 
3.0%
2023-088892
 
3.0%
2024-128887
 
3.0%
2023-098885
 
3.0%
2025-098883
 
3.0%
2024-078873
 
3.0%
2024-028872
 
3.0%
2025-078866
 
3.0%
Other values (24)211126
70.4%
2026-01-10T17:21:10.998304image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2644121
30.7%
0564824
26.9%
-300000
14.3%
3132612
 
6.3%
4132304
 
6.3%
5114475
 
5.5%
1105429
 
5.0%
826601
 
1.3%
626558
 
1.3%
926541
 
1.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)2100000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
2644121
30.7%
0564824
26.9%
-300000
14.3%
3132612
 
6.3%
4132304
 
6.3%
5114475
 
5.5%
1105429
 
5.0%
826601
 
1.3%
626558
 
1.3%
926541
 
1.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2100000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
2644121
30.7%
0564824
26.9%
-300000
14.3%
3132612
 
6.3%
4132304
 
6.3%
5114475
 
5.5%
1105429
 
5.0%
826601
 
1.3%
626558
 
1.3%
926541
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2100000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
2644121
30.7%
0564824
26.9%
-300000
14.3%
3132612
 
6.3%
4132304
 
6.3%
5114475
 
5.5%
1105429
 
5.0%
826601
 
1.3%
626558
 
1.3%
926541
 
1.3%
Distinct51
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:11.347813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters600000
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGA
2nd rowTN
3rd rowAR
4th rowMT
5th rowMA
ValueCountFrequency (%)
ca9240
 
3.1%
pa8511
 
2.8%
ny8254
 
2.8%
oh8085
 
2.7%
mi7906
 
2.6%
wi7883
 
2.6%
mn7513
 
2.5%
va7398
 
2.5%
fl7348
 
2.4%
tx7347
 
2.4%
Other values (41)220515
73.5%
2026-01-10T17:21:11.925169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A78267
13.0%
N66255
 
11.0%
M55350
 
9.2%
I51580
 
8.6%
C36285
 
6.0%
T34089
 
5.7%
O32009
 
5.3%
D26052
 
4.3%
L24729
 
4.1%
W22851
 
3.8%
Other values (14)172533
28.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)600000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A78267
13.0%
N66255
 
11.0%
M55350
 
9.2%
I51580
 
8.6%
C36285
 
6.0%
T34089
 
5.7%
O32009
 
5.3%
D26052
 
4.3%
L24729
 
4.1%
W22851
 
3.8%
Other values (14)172533
28.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)600000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A78267
13.0%
N66255
 
11.0%
M55350
 
9.2%
I51580
 
8.6%
C36285
 
6.0%
T34089
 
5.7%
O32009
 
5.3%
D26052
 
4.3%
L24729
 
4.1%
W22851
 
3.8%
Other values (14)172533
28.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)600000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A78267
13.0%
N66255
 
11.0%
M55350
 
9.2%
I51580
 
8.6%
C36285
 
6.0%
T34089
 
5.7%
O32009
 
5.3%
D26052
 
4.3%
L24729
 
4.1%
W22851
 
3.8%
Other values (14)172533
28.8%
Distinct51
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:12.279354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length20
Median length12
Mean length8.486273333
Min length4

Characters and Unicode

Total characters2545882
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGeorgia
2nd rowTennessee
3rd rowArkansas
4th rowMontana
5th rowMassachusetts
ValueCountFrequency (%)
new25069
 
7.0%
carolina12725
 
3.6%
virginia11750
 
3.3%
north10731
 
3.0%
south9689
 
2.7%
california9240
 
2.6%
pennsylvania8511
 
2.4%
york8254
 
2.3%
ohio8085
 
2.3%
michigan7906
 
2.2%
Other values (45)246472
68.8%
2026-01-10T17:21:12.821625image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a335657
13.2%
i253462
 
10.0%
n221381
 
8.7%
o200018
 
7.9%
s181759
 
7.1%
e163695
 
6.4%
r128196
 
5.0%
t95169
 
3.7%
l92032
 
3.6%
h76797
 
3.0%
Other values (36)797716
31.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)2545882
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a335657
13.2%
i253462
 
10.0%
n221381
 
8.7%
o200018
 
7.9%
s181759
 
7.1%
e163695
 
6.4%
r128196
 
5.0%
t95169
 
3.7%
l92032
 
3.6%
h76797
 
3.0%
Other values (36)797716
31.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)2545882
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a335657
13.2%
i253462
 
10.0%
n221381
 
8.7%
o200018
 
7.9%
s181759
 
7.1%
e163695
 
6.4%
r128196
 
5.0%
t95169
 
3.7%
l92032
 
3.6%
h76797
 
3.0%
Other values (36)797716
31.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)2545882
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a335657
13.2%
i253462
 
10.0%
n221381
 
8.7%
o200018
 
7.9%
s181759
 
7.1%
e163695
 
6.4%
r128196
 
5.0%
t95169
 
3.7%
l92032
 
3.6%
h76797
 
3.0%
Other values (36)797716
31.3%
Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:13.001078image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.610693333
Min length1

Characters and Unicode

Total characters483208
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row96
2nd row98
3rd row96
4th row98
5th row97
ValueCountFrequency (%)
9940552
13.5%
9833427
11.1%
9032356
10.8%
9430307
10.1%
128195
9.4%
224601
8.2%
9724554
8.2%
9620706
6.9%
719042
6.3%
511680
 
3.9%
Other values (5)34580
11.5%
2026-01-10T17:21:13.360687image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9223760
46.3%
743596
 
9.0%
441753
 
8.6%
837086
 
7.7%
032356
 
6.7%
628348
 
5.9%
128195
 
5.8%
224601
 
5.1%
512986
 
2.7%
310527
 
2.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)483208
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
9223760
46.3%
743596
 
9.0%
441753
 
8.6%
837086
 
7.7%
032356
 
6.7%
628348
 
5.9%
128195
 
5.8%
224601
 
5.1%
512986
 
2.7%
310527
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)483208
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
9223760
46.3%
743596
 
9.0%
441753
 
8.6%
837086
 
7.7%
032356
 
6.7%
628348
 
5.9%
128195
 
5.8%
224601
 
5.1%
512986
 
2.7%
310527
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)483208
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
9223760
46.3%
743596
 
9.0%
441753
 
8.6%
837086
 
7.7%
032356
 
6.7%
628348
 
5.9%
128195
 
5.8%
224601
 
5.1%
512986
 
2.7%
310527
 
2.2%
Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:13.569816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length29
Median length27
Mean length16.44853333
Min length7

Characters and Unicode

Total characters4934560
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAll Commercial
2nd rowElectric Power
3rd rowAll Commercial
4th rowElectric Power
5th rowAll Industrial
ValueCountFrequency (%)
power96090
13.9%
electric93978
13.6%
all85812
12.4%
non-chp76045
11.0%
industrial51238
7.4%
commercial43832
6.3%
chp41249
6.0%
sectors40552
5.9%
ipp35128
 
5.1%
sector32356
 
4.7%
Other values (6)95080
13.8%
2026-01-10T17:21:13.972760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e435354
 
8.8%
r418660
 
8.5%
l393832
 
8.0%
391360
 
7.9%
c335003
 
6.8%
o323100
 
6.5%
P313947
 
6.4%
t309786
 
6.3%
i254062
 
5.1%
n224475
 
4.5%
Other values (18)1534981
31.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)4934560
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e435354
 
8.8%
r418660
 
8.5%
l393832
 
8.0%
391360
 
7.9%
c335003
 
6.8%
o323100
 
6.5%
P313947
 
6.4%
t309786
 
6.3%
i254062
 
5.1%
n224475
 
4.5%
Other values (18)1534981
31.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)4934560
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e435354
 
8.8%
r418660
 
8.5%
l393832
 
8.0%
391360
 
7.9%
c335003
 
6.8%
o323100
 
6.5%
P313947
 
6.4%
t309786
 
6.3%
i254062
 
5.1%
n224475
 
4.5%
Other values (18)1534981
31.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)4934560
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e435354
 
8.8%
r418660
 
8.5%
l393832
 
8.0%
391360
 
7.9%
c335003
 
6.8%
o323100
 
6.5%
P313947
 
6.4%
t309786
 
6.3%
i254062
 
5.1%
n224475
 
4.5%
Other values (18)1534981
31.1%
Distinct45
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:14.268806image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.942866667
Min length2

Characters and Unicode

Total characters882860
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNGO
2nd rowWNT
3rd rowOBW
4th rowSUN
5th rowTPV
ValueCountFrequency (%)
all14447
 
4.8%
fos13504
 
4.5%
ren12943
 
4.3%
ngo12690
 
4.2%
ng12605
 
4.2%
aor12426
 
4.1%
pet11844
 
3.9%
pel11720
 
3.9%
dfo11544
 
3.8%
bio10001
 
3.3%
Other values (35)176276
58.8%
2026-01-10T17:21:14.718541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O123437
14.0%
N71073
 
8.1%
W65410
 
7.4%
S64786
 
7.3%
L62872
 
7.1%
P51595
 
5.8%
T48084
 
5.4%
G43177
 
4.9%
B42220
 
4.8%
R38300
 
4.3%
Other values (12)271906
30.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)882860
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
O123437
14.0%
N71073
 
8.1%
W65410
 
7.4%
S64786
 
7.3%
L62872
 
7.1%
P51595
 
5.8%
T48084
 
5.4%
G43177
 
4.9%
B42220
 
4.8%
R38300
 
4.3%
Other values (12)271906
30.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)882860
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
O123437
14.0%
N71073
 
8.1%
W65410
 
7.4%
S64786
 
7.3%
L62872
 
7.1%
P51595
 
5.8%
T48084
 
5.4%
G43177
 
4.9%
B42220
 
4.8%
R38300
 
4.3%
Other values (12)271906
30.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)882860
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
O123437
14.0%
N71073
 
8.1%
W65410
 
7.4%
S64786
 
7.3%
L62872
 
7.1%
P51595
 
5.8%
T48084
 
5.4%
G43177
 
4.9%
B42220
 
4.8%
R38300
 
4.3%
Other values (12)271906
30.8%
Distinct43
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:15.017466image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length40
Median length24
Mean length16.24845667
Min length4

Characters and Unicode

Total characters4874537
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rownatural gas & other gases
2nd rowonshore wind turbine
3rd rowbiomass
4th rowsolar
5th rowestimated total solar photovoltaic
ValueCountFrequency (%)
coal51042
 
7.1%
solar40691
 
5.6%
gas38980
 
5.4%
all34627
 
4.8%
other33766
 
4.7%
fuels27951
 
3.9%
petroleum26013
 
3.6%
natural25295
 
3.5%
waste25290
 
3.5%
photovoltaic23692
 
3.3%
Other values (45)392919
54.6%
2026-01-10T17:21:15.520462image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l519121
10.6%
a469407
 
9.6%
e437039
 
9.0%
420266
 
8.6%
o403263
 
8.3%
s390108
 
8.0%
t333242
 
6.8%
i288250
 
5.9%
r228750
 
4.7%
u198300
 
4.1%
Other values (18)1186791
24.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)4874537
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l519121
10.6%
a469407
 
9.6%
e437039
 
9.0%
420266
 
8.6%
o403263
 
8.3%
s390108
 
8.0%
t333242
 
6.8%
i288250
 
5.9%
r228750
 
4.7%
u198300
 
4.1%
Other values (18)1186791
24.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)4874537
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l519121
10.6%
a469407
 
9.6%
e437039
 
9.0%
420266
 
8.6%
o403263
 
8.3%
s390108
 
8.0%
t333242
 
6.8%
i288250
 
5.9%
r228750
 
4.7%
u198300
 
4.1%
Other values (18)1186791
24.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)4874537
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l519121
10.6%
a469407
 
9.6%
e437039
 
9.0%
420266
 
8.6%
o403263
 
8.3%
s390108
 
8.0%
t333242
 
6.8%
i288250
 
5.9%
r228750
 
4.7%
u198300
 
4.1%
Other values (18)1186791
24.3%

consumption-for-eg
Text

Missing 

Distinct38758
Distinct (%)14.4%
Missing31345
Missing (%)10.4%
Memory size4.6 MiB
2026-01-10T17:21:16.116642image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length1
Mean length3.177860081
Min length1

Characters and Unicode

Total characters853748
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14236 ?
Unique (%)5.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row.408
ValueCountFrequency (%)
0151964
56.6%
001345
 
0.1%
005304
 
0.1%
006303
 
0.1%
004280
 
0.1%
003260
 
0.1%
007260
 
0.1%
002255
 
0.1%
008249
 
0.1%
009234
 
0.1%
Other values (38709)114201
42.5%
2026-01-10T17:21:16.932224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0199994
23.4%
.116544
13.7%
185988
10.1%
266711
 
7.8%
360849
 
7.1%
458932
 
6.9%
555603
 
6.5%
654087
 
6.3%
752913
 
6.2%
852085
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)853748
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0199994
23.4%
.116544
13.7%
185988
10.1%
266711
 
7.8%
360849
 
7.1%
458932
 
6.9%
555603
 
6.5%
654087
 
6.3%
752913
 
6.2%
852085
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)853748
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0199994
23.4%
.116544
13.7%
185988
10.1%
266711
 
7.8%
360849
 
7.1%
458932
 
6.9%
555603
 
6.5%
654087
 
6.3%
752913
 
6.2%
852085
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)853748
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0199994
23.4%
.116544
13.7%
185988
10.1%
266711
 
7.8%
360849
 
7.1%
458932
 
6.9%
555603
 
6.5%
654087
 
6.3%
752913
 
6.2%
852085
 
6.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:17.102859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length23
Median length23
Mean length20.57463667
Min length12

Characters and Unicode

Total characters6172391
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowthousand Mcf
2nd rowthousand physical units
3rd rowthousand physical units
4th rowthousand physical units
5th rowthousand physical units
ValueCountFrequency (%)
thousand300000
35.5%
physical187797
22.2%
units187797
22.2%
short56248
 
6.7%
tons56248
 
6.7%
barrels28222
 
3.3%
mcf27733
 
3.3%
2026-01-10T17:21:17.525783image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)6172391
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)6172391
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)6172391
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%
Distinct70329
Distinct (%)26.2%
Missing31345
Missing (%)10.4%
Memory size4.6 MiB
2026-01-10T17:21:18.205476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.379107033
Min length1

Characters and Unicode

Total characters1445124
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35622 ?
Unique (%)13.3%

Sample

1st row0
2nd row.00178
3rd row0
4th row.05202
5th row.00238
ValueCountFrequency (%)
047679
 
17.7%
00002853
 
0.3%
00001800
 
0.3%
00003577
 
0.2%
00004533
 
0.2%
00005507
 
0.2%
00007404
 
0.2%
00006404
 
0.2%
00008381
 
0.1%
0002331
 
0.1%
Other values (70318)216186
80.5%
2026-01-10T17:21:19.130700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0269410
18.6%
.220975
15.3%
1150410
10.4%
2122913
8.5%
3110954
7.7%
4102692
 
7.1%
598903
 
6.8%
696004
 
6.6%
793221
 
6.5%
890658
 
6.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)1445124
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0269410
18.6%
.220975
15.3%
1150410
10.4%
2122913
8.5%
3110954
7.7%
4102692
 
7.1%
598903
 
6.8%
696004
 
6.6%
793221
 
6.5%
890658
 
6.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1445124
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0269410
18.6%
.220975
15.3%
1150410
10.4%
2122913
8.5%
3110954
7.7%
4102692
 
7.1%
598903
 
6.8%
696004
 
6.6%
793221
 
6.5%
890658
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1445124
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0269410
18.6%
.220975
15.3%
1150410
10.4%
2122913
8.5%
3110954
7.7%
4102692
 
7.1%
598903
 
6.8%
696004
 
6.6%
793221
 
6.5%
890658
 
6.3%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:19.329635image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters3900000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowmillion MMBtu
2nd rowmillion MMBtu
3rd rowmillion MMBtu
4th rowmillion MMBtu
5th rowmillion MMBtu
ValueCountFrequency (%)
million300000
50.0%
mmbtu300000
50.0%
2026-01-10T17:21:19.691708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)3900000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3900000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3900000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%

cost
Text

Missing 

Distinct3962
Distinct (%)6.8%
Missing241811
Missing (%)80.6%
Memory size4.6 MiB
2026-01-10T17:21:20.376828image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length1
Mean length1.800374641
Min length1

Characters and Unicode

Total characters104762
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1293 ?
Unique (%)2.2%

Sample

1st row0
2nd row0
3rd row0
4th row4.51
5th row0
ValueCountFrequency (%)
046002
79.1%
2.8129
 
< 0.1%
2.5628
 
< 0.1%
2.7627
 
< 0.1%
3.0327
 
< 0.1%
2.7126
 
< 0.1%
3.326
 
< 0.1%
2.5126
 
< 0.1%
2.3525
 
< 0.1%
2.6125
 
< 0.1%
Other values (3948)11948
 
20.5%
2026-01-10T17:21:21.305077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
049075
46.8%
.12071
 
11.5%
17951
 
7.6%
25768
 
5.5%
35681
 
5.4%
44704
 
4.5%
54106
 
3.9%
63983
 
3.8%
73852
 
3.7%
93794
 
3.6%
Other values (2)3777
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)104762
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
049075
46.8%
.12071
 
11.5%
17951
 
7.6%
25768
 
5.5%
35681
 
5.4%
44704
 
4.5%
54106
 
3.9%
63983
 
3.8%
73852
 
3.7%
93794
 
3.6%
Other values (2)3777
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)104762
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
049075
46.8%
.12071
 
11.5%
17951
 
7.6%
25768
 
5.5%
35681
 
5.4%
44704
 
4.5%
54106
 
3.9%
63983
 
3.8%
73852
 
3.7%
93794
 
3.6%
Other values (2)3777
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)104762
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
049075
46.8%
.12071
 
11.5%
17951
 
7.6%
25768
 
5.5%
35681
 
5.4%
44704
 
4.5%
54106
 
3.9%
63983
 
3.8%
73852
 
3.7%
93794
 
3.6%
Other values (2)3777
 
3.6%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:21.551782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length26
Median length26
Mean length23.57463667
Min length15

Characters and Unicode

Total characters7072391
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdollars per Mcf
2nd rowdollars per physical units
3rd rowdollars per physical units
4th rowdollars per physical units
5th rowdollars per physical units
ValueCountFrequency (%)
dollars300000
26.2%
per300000
26.2%
physical187797
16.4%
units187797
16.4%
short56248
 
4.9%
tons56248
 
4.9%
barrels28222
 
2.5%
mcf27733
 
2.4%
2026-01-10T17:21:22.015599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
844045
11.9%
s816312
11.5%
l816019
11.5%
r712692
10.1%
a516019
 
7.3%
p487797
 
6.9%
o412496
 
5.8%
i375594
 
5.3%
e328222
 
4.6%
t300293
 
4.2%
Other values (9)1462902
20.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)7072391
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
844045
11.9%
s816312
11.5%
l816019
11.5%
r712692
10.1%
a516019
 
7.3%
p487797
 
6.9%
o412496
 
5.8%
i375594
 
5.3%
e328222
 
4.6%
t300293
 
4.2%
Other values (9)1462902
20.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)7072391
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
844045
11.9%
s816312
11.5%
l816019
11.5%
r712692
10.1%
a516019
 
7.3%
p487797
 
6.9%
o412496
 
5.8%
i375594
 
5.3%
e328222
 
4.6%
t300293
 
4.2%
Other values (9)1462902
20.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)7072391
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
844045
11.9%
s816312
11.5%
l816019
11.5%
r712692
10.1%
a516019
 
7.3%
p487797
 
6.9%
o412496
 
5.8%
i375594
 
5.3%
e328222
 
4.6%
t300293
 
4.2%
Other values (9)1462902
20.7%

generation
Text

Missing 

Distinct104050
Distinct (%)36.3%
Missing13549
Missing (%)4.5%
Memory size4.6 MiB
2026-01-10T17:21:22.855726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length11
Median length9
Mean length6.404680033
Min length1

Characters and Unicode

Total characters1834627
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52399 ?
Unique (%)18.3%

Sample

1st row0
2nd row.523
3rd row0
4th row15.245
5th row7.69581
ValueCountFrequency (%)
046392
 
16.2%
002284
 
0.1%
003232
 
0.1%
001222
 
0.1%
004200
 
0.1%
005123
 
< 0.1%
006112
 
< 0.1%
01105
 
< 0.1%
00799
 
< 0.1%
01984
 
< 0.1%
Other values (103378)238598
83.3%
2026-01-10T17:21:23.805430image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
.240016
13.1%
1207782
11.3%
2177910
9.7%
0176413
9.6%
3162649
8.9%
4154716
8.4%
5147059
8.0%
6145134
7.9%
7141113
7.7%
8138860
7.6%
Other values (2)142975
7.8%

Most occurring categories

ValueCountFrequency (%)
(unknown)1834627
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
.240016
13.1%
1207782
11.3%
2177910
9.7%
0176413
9.6%
3162649
8.9%
4154716
8.4%
5147059
8.0%
6145134
7.9%
7141113
7.7%
8138860
7.6%
Other values (2)142975
7.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1834627
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
.240016
13.1%
1207782
11.3%
2177910
9.7%
0176413
9.6%
3162649
8.9%
4154716
8.4%
5147059
8.0%
6145134
7.9%
7141113
7.7%
8138860
7.6%
Other values (2)142975
7.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1834627
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
.240016
13.1%
1207782
11.3%
2177910
9.7%
0176413
9.6%
3162649
8.9%
4154716
8.4%
5147059
8.0%
6145134
7.9%
7141113
7.7%
8138860
7.6%
Other values (2)142975
7.8%

generation-units
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:24.003848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters6600000
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowthousand megawatthours
2nd rowthousand megawatthours
3rd rowthousand megawatthours
4th rowthousand megawatthours
5th rowthousand megawatthours
ValueCountFrequency (%)
thousand300000
50.0%
megawatthours300000
50.0%
2026-01-10T17:21:24.353143image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t900000
13.6%
a900000
13.6%
h600000
9.1%
o600000
9.1%
u600000
9.1%
s600000
9.1%
n300000
 
4.5%
d300000
 
4.5%
300000
 
4.5%
m300000
 
4.5%
Other values (4)1200000
18.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)6600000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t900000
13.6%
a900000
13.6%
h600000
9.1%
o600000
9.1%
u600000
9.1%
s600000
9.1%
n300000
 
4.5%
d300000
 
4.5%
300000
 
4.5%
m300000
 
4.5%
Other values (4)1200000
18.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)6600000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t900000
13.6%
a900000
13.6%
h600000
9.1%
o600000
9.1%
u600000
9.1%
s600000
9.1%
n300000
 
4.5%
d300000
 
4.5%
300000
 
4.5%
m300000
 
4.5%
Other values (4)1200000
18.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)6600000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t900000
13.6%
a900000
13.6%
h600000
9.1%
o600000
9.1%
u600000
9.1%
s600000
9.1%
n300000
 
4.5%
d300000
 
4.5%
300000
 
4.5%
m300000
 
4.5%
Other values (4)1200000
18.2%

total-consumption
Text

Missing 

Distinct41189
Distinct (%)15.3%
Missing31345
Missing (%)10.4%
Memory size4.6 MiB
2026-01-10T17:21:24.959690image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length10
Median length1
Mean length3.270506784
Min length1

Characters and Unicode

Total characters878638
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15111 ?
Unique (%)5.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row3.499
ValueCountFrequency (%)
0150871
56.2%
001294
 
0.1%
003247
 
0.1%
002236
 
0.1%
005227
 
0.1%
006214
 
0.1%
012204
 
0.1%
004194
 
0.1%
009185
 
0.1%
01176
 
0.1%
Other values (41150)115807
43.1%
2026-01-10T17:21:25.823563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0199412
22.7%
.117679
13.4%
189887
10.2%
269222
 
7.9%
363638
 
7.2%
461432
 
7.0%
558346
 
6.6%
656805
 
6.5%
754939
 
6.3%
854002
 
6.1%

Most occurring categories

ValueCountFrequency (%)
(unknown)878638
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0199412
22.7%
.117679
13.4%
189887
10.2%
269222
 
7.9%
363638
 
7.2%
461432
 
7.0%
558346
 
6.6%
656805
 
6.5%
754939
 
6.3%
854002
 
6.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown)878638
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0199412
22.7%
.117679
13.4%
189887
10.2%
269222
 
7.9%
363638
 
7.2%
461432
 
7.0%
558346
 
6.6%
656805
 
6.5%
754939
 
6.3%
854002
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown)878638
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0199412
22.7%
.117679
13.4%
189887
10.2%
269222
 
7.9%
363638
 
7.2%
461432
 
7.0%
558346
 
6.6%
656805
 
6.5%
754939
 
6.3%
854002
 
6.1%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:26.027859image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length23
Median length23
Mean length20.57463667
Min length12

Characters and Unicode

Total characters6172391
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowthousand Mcf
2nd rowthousand physical units
3rd rowthousand physical units
4th rowthousand physical units
5th rowthousand physical units
ValueCountFrequency (%)
thousand300000
35.5%
physical187797
22.2%
units187797
22.2%
short56248
 
6.7%
tons56248
 
6.7%
barrels28222
 
3.3%
mcf27733
 
3.3%
2026-01-10T17:21:26.425082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)6172391
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)6172391
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)6172391
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s816312
13.2%
t600293
9.7%
h544045
8.8%
544045
8.8%
n544045
8.8%
a516019
8.4%
u487797
7.9%
o412496
 
6.7%
i375594
 
6.1%
d300000
 
4.9%
Other values (9)1031745
16.7%

total-consumption-btu
Text

Missing 

Distinct75261
Distinct (%)28.0%
Missing31345
Missing (%)10.4%
Memory size4.6 MiB
2026-01-10T17:21:27.034345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length9
Median length6
Mean length5.4470008
Min length1

Characters and Unicode

Total characters1463364
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38261 ?
Unique (%)14.2%

Sample

1st row0
2nd row.00178
3rd row0
4th row.05202
5th row.02032
ValueCountFrequency (%)
046223
 
17.2%
00001770
 
0.3%
00002750
 
0.3%
00004438
 
0.2%
00006418
 
0.2%
00005409
 
0.2%
00008396
 
0.1%
00003390
 
0.1%
00007335
 
0.1%
0002284
 
0.1%
Other values (75251)218242
81.2%
2026-01-10T17:21:27.914572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0250947
17.1%
.222432
15.2%
1155850
10.7%
2125858
8.6%
3115713
7.9%
4106383
7.3%
5102135
7.0%
699874
 
6.8%
797356
 
6.7%
894287
 
6.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)1463364
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0250947
17.1%
.222432
15.2%
1155850
10.7%
2125858
8.6%
3115713
7.9%
4106383
7.3%
5102135
7.0%
699874
 
6.8%
797356
 
6.7%
894287
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)1463364
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0250947
17.1%
.222432
15.2%
1155850
10.7%
2125858
8.6%
3115713
7.9%
4106383
7.3%
5102135
7.0%
699874
 
6.8%
797356
 
6.7%
894287
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)1463364
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0250947
17.1%
.222432
15.2%
1155850
10.7%
2125858
8.6%
3115713
7.9%
4106383
7.3%
5102135
7.0%
699874
 
6.8%
797356
 
6.7%
894287
 
6.4%
Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.6 MiB
2026-01-10T17:21:28.103922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length13
Median length13
Mean length13
Min length13

Characters and Unicode

Total characters3900000
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowmillion MMBtu
2nd rowmillion MMBtu
3rd rowmillion MMBtu
4th rowmillion MMBtu
5th rowmillion MMBtu
ValueCountFrequency (%)
million300000
50.0%
mmbtu300000
50.0%
2026-01-10T17:21:28.449411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)3900000
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)3900000
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)3900000
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i600000
15.4%
l600000
15.4%
M600000
15.4%
m300000
7.7%
n300000
7.7%
o300000
7.7%
300000
7.7%
B300000
7.7%
t300000
7.7%
u300000
7.7%